FRBPSO: A Fuzzy Rule Based Binary PSO for Feature Selection

Particle swarm optimization and fuzzy logic have shown their fruits for many years across the fields of science. Fuzzy logic acts as an intelligent layer to any conventional system. Recently fuzzy logic has been used to improve the performance of particle swarm optimization (PSO). This paper presents a novel fuzzy rule based binary PSO (FRBPSO) for feature selection to get better classification and a survey on the PSO fuzzy logic hybrid methods. The results on benchmarking high dimensional microarray datasets show the merits of the proposed FRBPSO method.

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